A Dynamic Event‐Triggered H∞ Fault Detection Approach for T‐S Fuzzy Systems

The problem of dynamic event‐triggered fault detection (FD) for Takagi‐Sugeno (T‐S) fuzzy systems is investigated in this paper. First, the FD issue is formulated as a specific minimum problem for an indefinite quadratic form. Then, by constructing an equivalent Krein space stochastic system, sufficient and necessary conditions for the existence of a minimum are derived through Krein space projection and innovation analysis. Subsequently, a solution to the dynamic event‐triggered fault detection filter (FDF) is obtained via Riccati recursions. The proposed ‐FDF incorporates residual feedback to improve FD performance. Moreover, the obtained residual signal is completely decoupled from the event‐triggered transmission error. This decoupling allows the ‐FDF and the dynamic event‐triggering mechanism to be implemented independently. Thus, the proposed Krein space‐based FD approach is less conservative and easier to implement than existing linear matrix inequality‐based event‐triggered FD methods for T‐S fuzzy systems. Finally, the effectiveness of the proposed method is verified using a three‐tank system.